Interview: Serge Kassibrakis, PhD, Head of Quantitative Asset Management at Swissquote

Robots will incorporate Artificial Intelligence

« Three years ago in this very magazine, Paolo Buzzi, CTO and co-founder of Swissquote, discussed the rise of robo-advisors and predicted a future where every large bank would have its own algorithm. So now, in today’s world, what progress has been made? How has this aspect of fintech evolved? We wanted to get an update from Serge Kassibrakis, Head of Quantitative Asset Management at Swissquote. ».

BSL: The term “uberisation” was included in the dictionary in 2017 with the following definition: “To transform (an industry sector) with an innovative business model based on digital technology...”. Has Swissquote become the Uber of finance with its robo-advisor?

SK: I would say that since the very beginning, and guided by the vision of its two founders, Swissquote has continually transformed entire swathes of the banking industry: free and instant access to information, direct access to the stock exchange, and as of a few years ago with its robo-advisor, direct access to algorithms that were previously only available to professionals. However, it must be pointed out that the word “uberisation” often has a negative connotation. I often find that using this word puts me at odds with professionals, whereas I’m trying to create connections and benefit from synergies that seem obvious to me.

I realised that this wariness from many professionals, asset managers and private bankers came from a disconnect between what they thought a robo-advisor would be and what it actually is. No, the robot doesn’t do everything itself! It needs to be told what to do, based on objectives, constraints and even market perspectives – as the Swissquote robot does. Once these parameters are set, the robot will know better than anyone how to implement all this data within a portfolio. It’s a bit like an aeroplane autopilot – seasoned pilots Marc Bürki and Paolo Buzzi would agree with this comparison. An autopilot is incredibly sophisticated but if you don’t tell it where to go and how to get there, it won’t go anywhere at all. 

BSL: So where are we in the revolution, if there is one at all?

SK: There is indeed a revolution, but not where we think! The revolution doesn’t lie in the portfolio optimisation algorithms that we’ve all known about for a long time, even though they are continuously improving. The revolution lies in the fact that only ten years ago, only large financial institutions could operate these algorithms; they needed very powerful and expensive machines and IT knowledge, so only professionals had access to them. Today, I can access the processing power and algorithms on my PC or my smartphone, especially with Swissquote, where all of the algorithm parameters are available to clients. For “retail” clients with specific terms, it means it’s very easy to create a bespoke strategy. For people with less time to spend on their portfolios, pre-determined and less personalised strategies are available. Finally, for asset managers and private bankers, this is an incredible automation tool – it’s what we call the hybrid model. We’ve also partnered with several professional managers who recognise how useful this tool is. 

BSL: So why did Swissquote decide to put its robot on the market, even as a white label?

SK: It makes sense for this reason: unlike almost all of our competitors, we’re not offering ten pre-defined portfolios. The parameters are completely open and clients are able to customise their portfolios entirely.

So that opens doors to the partnerships I just mentioned, because who better than a professional to help people who don’t have the time to actually set these parameters? Regardless of the number of partnerships, the portfolios generated will all be different because they will incorporate the specific requirements of each client, as well as input from partnering asset managers and private bankers. 

What’s more, remaining in constant contact with these professionals helps us to envision future projects. Finally, the power of automation helps our partners to expand their client base, as they can now accept assets under management that are below the old model’s profitability threshold.  

BSL: So what developments can we expect from the robots in the near future?

SK: I can say without hesitation that robots will increasingly incorporate artificial intelligence modules. This trend isn’t going to stop any time soon. These modules will be able to better assist clients in choosing and updating their parameters, by predicting for example that a client’s risk aversion might change significantly. Robots can assist with the management part of the portfolio as well, by considerably strengthening current “rules-based” algorithms. That will require more and more data and processing power. On this last point, there are many potential avenues. One example I would give is semantic analysis of financial information or any other text-based sources. It can identify an overall impression of a listed company or an industry by analysing an enormous amount of text. Many start-ups have been working on this, and the results are starting to come to light. Thanks to partnerships with EPFL, we’re closely involved in all of this research.